Zimmermann Stochastic Discrete Event Systems

Modeling, Evaluation, Applications
2008
ISBN: 978-3-540-74173-2
Verlag: Springer
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 392 Seiten, eBook

Stochastic discrete-event systems (SDES) capture the randomness in choices due to activity delays and the probabilities of decisions.

This book delivers a comprehensive overview on modeling with a quantitative evaluation of SDES. It presents an abstract model class for SDES as a pivotal unifying result and details important model classes. The book also includes nontrivial examples to explain real-world applications of SDES.

Zielgruppe

Research

Autoren/Hrsg.

Zimmermann, Armin

Inhaltsverzeichnis

Modeling.- A Unified Description for Stochastic Discrete Event Systems.- Stochastic Timed Automata.- Queuing Models.- Simple Petri Nets.- Colored Petri Nets.- Evaluation.- Standard Quantitative Evaluation Methods for SDES.- An Iterative Approximation Method.- Efficient Simulation of SDES Models.- System Optimization.- Model-Based Direct Control.- Software Tool Support.- Applications.- Optimization of a Manufacturing System.- Communication System Performability Evaluation.- Supply Chain Performance Evaluation and Design.- Model-Based Design and Control of a Production Cell.- Summary and Outlook.

Über Autor(innen)

Since fall 2006 Armin Zimmermann has held a deputy professorship for real-time systems and robotics at the faculty of electrical engineering and computer sciences of TU Berlin. He is the principal investigator of the research group Model-Based Evaluation of Discrete Real-Time Systems and coordinates the graduate college "Stochastic Modelling and Quantitative Analysis of Complex Systems in Engineering". Prior to that, he was research fellow from 1995 to 1999 and research assistant from 1999 to 2006 at TU Berlin. In 1997, he had received the Krone award, the Carl Ramsauer award, and the Chorafas Foundation award for his thesis on modelling and analysis of manufacturing systems with Petri nets.

His research interests include modelling, performance evaluation, optimization, and control of technical systems using discrete-event models as well as their tool support.